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An Introduction to Applied Multivariate Analysis with R by Brian Everitt: Used
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Specificaties
- Objectstaat
- Book Title
- An Introduction to Applied Multivariate Analysis with R
- Publication Date
- 2011-05-03
- Pages
- 274
- ISBN
- 9781441996497
Over dit product
Product Identifiers
Publisher
Springer New York
ISBN-10
1441996494
ISBN-13
9781441996497
eBay Product ID (ePID)
109027425
Product Key Features
Number of Pages
Xiv, 274 Pages
Publication Name
Introduction to Applied Multivariate Analysis with R
Language
English
Subject
Programming Languages / General, Probability & Statistics / Multivariate Analysis, Probability & Statistics / General
Publication Year
2011
Type
Textbook
Subject Area
Mathematics, Computers
Series
Use R! Ser.
Format
Trade Paperback
Dimensions
Item Weight
16 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Intended Audience
Scholarly & Professional
TitleLeading
An
Dewey Edition
22
Reviews
From the book reviews: "This practical book provides a well-organized summary of popular multivariate data analysis techniques with practical examples. As the book title indicates, all introduced techniques are accompanied by relevant and friendly R codes, and thus it can be used for excellent R programming reference for those who wish to use R for multivariate data analysis." (Technometrics, Vol. 54 (4), November, 2012), "This book covers basic to advanced approaches for the analysis of multivariate data in R. ... All chapters end with a summary and exercises, making this book an excellent addition to applied statistics courses. The approach, numerous examples and fragments of code make it accessible to undergraduate and postgraduate students alike, as well as researchers ... ." (Irina Ioana Mohorianu, zbMATH 1306.62010, 2015) "Each chapter introduces briefly the theory on well-known methods to analyze multivariate data and then focuses on the application of the multivariate techniques to example data with R. ... addressed to students in applied statistics courses or applied statisticians looking for a valuable educational textbook on multivariate analysis. ... an ideal textbook for students or persons, employed in the field of applied statistics, who wish to study the analysis of multivariate data and to apply multivariate techniques to real data." (Wiebke Werft, Biometrical Journal, Vol. 55 (6), 2013) "This practical book provides a well-organized summary of popular multivariate data analysis techniques with practical examples. As the book title indicates, all introduced techniques are accompanied by relevant and friendly R codes, and thus it can be used for excellent R programming reference for those who wish to use R for multivariate data analysis." (Technometrics, Vol. 54 (4), November, 2012)
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
519.535
Table Of Content
Multivariate data and multivariate analysis.- Looking at multivariate data: visualization.- Principal components analysis.- Multidimensional scaling.- Exploratory factor analysis.- Cluster analysis.- Confirmatory factor analysis and structural equation models.- The analysis of repeated measures data.-
Synopsis
The majority of data sets collected by researchers in all disciplines are multivariate. This book comprehensively covers a variety of multivariate analysis techniques using R. It provides extensive examples of R code used to apply the multivariate techniques., The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data., Multivariate data and multivariate analysis.- Looking at multivariate data: visualization.- Principal components analysis.- Multidimensional scaling.- Exploratory factor analysis.- Cluster analysis.- Confirmatory factor analysis and structural equation models.- The analysis of repeated measures data.-
LC Classification Number
QA276-280
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